Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Source code duplication, commonly known as code cloning , is considered an obstacle to software maintenance because changes to a cloned region often require consistent changes to other regions of the source code. Research has provided evidence that the elimination of clones may not always be practical, feasible, or cost-effective. We present a clone management approach that describes clone regions in a robust way that is independent from the exact text of clone regions or their location in a file, and that provides support for tracking clones in evolving software. Our technique relies on the concept of abstract clone region descriptors (CRDs), which describe clone regions using a combination of their syntactic, structural, and lexical information. We present our definition of CRDs, and describe a clone tracking system capable of producing CRDs from the output of different clone detection tools, notifying developers of modifications to clone regions, and supporting updates to the documented clone relationships. We evaluated the performance and usefulness of our approach across three clone detection tools and five subject systems, and the results indicate that CRDs are a practical and robust representation for tracking code clones in evolving software.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it